Indian Society for Heat and Mass Transfer

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Proceedings of the 25th National and 3rd International ISHMT-ASTFE Heat and Mass Transfer Conference (IHMTC-2019)

ISSN: 2688-7231 (Online)

Modelling and Simulation of Radio Frequency Ablation for Liver Tumors and Performance Analysis using Crossed Array Design of Experiments Approach

Sandeep Sulake
Department of Mechanical Engineering, BITS Pilani Hyderabad Campus

Satish Kumar Dubey
Department of Mechanical Engineering, BITS Pilani Hyderabad Campus

Arshad Javed
Department of Mechanical Engineering, BITS Pilani Hyderabad Campus

DOI: 10.1615/IHMTC-2019.1310
pages 781-786


Numerical Simulations have been performed to study the efficacy of Radio Frequency Ablation (RFA) on liver tumors. A cylindrical shaped liver domain and spherical tumor with a multi-tine radio frequency electrode is modelled for this purpose. Fraction of necrotic tissue (FNT) is simulated using bio heat transfer coupled with electric currents on COMSOL multiphysics software. The simulation results are validated with published experimental data. Temperature controlled radio frequency ablation procedure is carried out by implementing a proportional integral derivative (PID) controller to limit the temperature in the target tissue to a desired value. Significance of tolerance ranges of three different critical parameters namely target tip temperature, blood perfusion rate of tumor and blood perfusion rate of surrounding liver tissue are investigated. Tolerance ranges for each critical parameter are chosen and grouped into two levels as tight and loose tolerances. Crossed Array Design of Experiments (CA-DOE) approach is utilized for forming inner and outer orthogonal arrays. The effect of each combination formed is investigated by simulating FNT, which is considered as a response parameter in this study. Obtained responses for different combinations are analysed using various statistical techniques like Analysis of Mean (ANOM), Analysis of Variance (ANOVA), signal to noise ratio etc., which is be helpful to identify the robust design combinations and help clinicians to perform RFA on liver tumors with high efficacy.

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